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A group consists of courses that have the same role in a study plan. A group thus facilitates the requirement on credits to be acquired in a prescribed structure for a study plan. Hence, a student just cannot accumulate the required amount of credits required by the study plan; s/he must meet the requirements of each group of courses of a given study plan.
       Each student has to complete either at least a prescribed minimum (amount of) credits or to successfully complete a prescribed minimum (amount of) courses for a given group.
If a group has defined a minimum amount of credits = total amount of credits that can be obtained from the group, the student must successfully complete all the courses of the group. Such a group of courses has its role marked as 'compulsory'. If a group has defined a minimum amount of credits < total amount of credits obtainable from the group, such a situation is referred to as a group with an obligation to choose and complete at least the minimally set amount of credits. Similarly for courses.
If a group has defined a minimum amount of credits = 0 and a minimum number of courses = 0 at the same time, then the courses in the given group are elective.
Ifa a group has defined a minimum amount of credits < maximum amount of credits < total amount of credits obtainable from the group, then credits earned earned above the minimum amount of credits are seen as elective and credits above the maximum amount of credits from a given group do not count.
For ease of reference, each group has a role of the courses in the given study plan assigned next to its name.
The list is sorted alphabetically by the Department code and Course title.
Group: Purely Elective Master Courses, Version 2017
Min. credits: 0   Credits total: 0   Min. courses: 0 Role: V - elective courses
Course Course title Extend of
teaching
Comple-
tion
Seme-
ster
Recomm.
sem.
Cre-
dits
Instruc-
tor
Cat.
MI-ROZ.16 Pattern Recognition 2P+1C Z,ZK Z 1 5 18101
MI-ZS10 Master internship abroad for 10 credits Z Z,L 10 18000
MI-ZS20 Master internship abroad for 20 credits Z Z,L 20 18000
MI-ZS30 Master internship abroad for 30 credits Z Z,L 30 18000
NI-VPR Research Project Z Z,L 5 18000
MI-PAM Efficient Preprocessing and Parameterized Algorithms 2P+1C Z,ZK L 4 18101
MI-LOM.16 Linear Optimization and Methods 2P+1C Z,ZK Z 5 18101
MI-TS3 Theoretical Seminar Master III 2C Z Z 4 18101
MI-TS2 Theoretical Seminar Master II 2C Z L 4 18101
MI-TS4 Theoretical Seminar Master IV 2C Z L 4 18101
MI-TS1 Theoretical Seminar Master I 2C Z Z 4 18101
MI-DNP Advanced .NET 2P+1C Z,ZK Z 4 18102
MI-PYT Advanced Python 3C KZ Z 4 18102
MI-PVR Advanced Virtual Reality 2P+1C KZ Z 4 18102
NI-PG1 Computer Grafics 1 2P+1C ZK L 4 18102
NI-CCC Creative Coding and Computational Art 1P+2C KZ Z,L 4 Kortán J., Richtr R. 18102
MI-DSP Database Systems in Practes 2P+1C Z,ZK L 4 18102
NI-MOP Modern Object-Oriented Programming in Pharo 3C KZ Z 4 Blizničenko J. 18102
MI-PSL Programming in Scala 2P+1C Z,ZK L 4 18102
MI-PVS Advanced embedded systems 2P+2C Z,ZK Z 4 18103
MI-SCE2 Computer Engineering Seminar Master II 2C Z L,Z 4 18103
MI-SCE1 Computer Engineering Seminar Master I 2C Z L,Z 4 18103
MI-IVS Intelligent embedded systems 1P+3C KZ L 4 18103
MI-OLI Linux Drivers 2P+2C Z,ZK L 4 18103
PI-SCN Seminars on Digital Design 2P+1C ZK Z,L 4 18103
NI-HSC Side-Channel Analysis in Hardware 2P+2C Z,ZK Z 4 Miškovský V., Socha P. 18103
NI-IAM Internet and Multimedia 2P+1C Z,ZK L 4 18104
BI-SOJ Machine Oriented Languages 2P+2C Z,ZK L 4 18104
MI-MCS Multicore Systems 1P+2C KZ Z 4 18104
MI-PRC Programming in CUDA 2P+1C Z,ZK L 4 18104
NI-AML Advanced machine learning 2P + 1C Z,ZK L 5 18105
MI-VYC Computability 2P+2C Z,ZK L 4 18105
MI-DDM Distributed Data Mining 3C KZ L 4 18105
MI-GLR Games and reinforcement learning 2P+2C Z,ZK L 4 18105
MI-HMI2 History of Mathematics and Informatics 2P+1C ZK Z 3 18105
MI-IKM Internet and Classification Methods 1P+1C Z,ZK L 4 18105
MI-SZ1 Knowledge Engineering Seminar Master I 2C Z L,Z 4 18105
MI-MSI Mathematical Structures in Computer Science 2P+1C Z,ZK L 4 18105
MI-MZI Mathematics for data science 2P+1C Z,ZK L 4 18105
MI-SCR Statistical Analysis of Time Series 2P+1C Z,ZK Z 4 18105
NI-LSM Statistical Modelling Lab 3C KZ L 5 18105
MI-TNN Theory of Neural Networks 1P+1C Z,ZK L 4 18105
MI-ATH Combinatorial Theories of Games 2P+2C Z,ZK L 2 4 18101
MI-AFP Applied Functional Programming 2P+1C KZ L 2 5 18102
MI-IOS Advanced techniques in iOS applications 2P+2C KZ L 2 4 18102
MI-DZO Digital Image Processing 2P+1C Z,ZK L 2 4 18102
MI-RUB Programming in Ruby 3C KZ Z 2 4 18102
MI-VEM Scientific thinking 1P+1C KZ L 2 2 18102
MI-IOT Internet of Things 2P+1C Z,ZK L 2 4 18104
MI-MAI Multimedia and Internet 2P+1C Z,ZK L 2 3 18104
MI-RRI Risk Management in Informatics 2P ZK L 2 3 18104
MI-BPS Wireless Computer Networks 2P+1C Z,ZK L 2 4 18104
MI-APH Architecture of computer games 2P+1C Z,ZK Z 3 4 18102
MI-MPC Modern programming in C ++ 2P+1C Z,ZK Z 3 5 18102
MI-ARI Computer arithmetic 2P+1C Z,ZK Z,L 3 4 18103
MI-BML Bayesian Methods for Machine Learning 2P+1C KZ L 4 5 18105

Vedle zde uvedených předmětů si jako volitelný můžete zapsat kterýkoliv předmět, který se nabízí v rámci vašeho studijního programu a formy studia, který jste si nezapsal(a) jako povinný předmět programu/oboru/zaměření nebo povinně volitelný předmět.
Předměty této skupiny, které student absolvoval v bakalářském studiu na ČVUT, nelze znovu absolvovat v magisterském studiu.

Page updated 12. 10. 2024, semester: L/2019-20, L/2022-3, L/2020-1, Z/2023-4, Z/2019-20, Z/2021-2, Z/2020-1, Z/2024-5, L/2021-2, Z/2022-3, L/2023-4, Send comments to the content presented here toAdministrator of study plans Design and implementation: J. Novák, I. Halaška